Samenvatting
Summary Kennismaking met onderzoeksmethoden en statistiek: Experimenteel en Integriteit
Dit is een samenvatting met alle begrippen van de experimenteel onderzoek en integriteit uit het KOM boek.
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Chapter 4: ethical principlesThree principles of Belmont report (APA)
• Beneficence (and nonmaleficence) – treat people in a way that will benefit them
• Justice – strive to treat all people fairly (be aware of biases)
• Respect for people’s rights and dignity – protect people’s rights such as privacy, right to give
consent and right to be treated confidentially.
Institutional review board (IRB) – a committee responsible for interpreting ethical principles and
ensuring that research using human participants is conducted ethically.
Deception – deceiving people in an experiment to get an objective representation of the wanted
behavior.
Omission – withholding details of the study from participants.
Commission – actively lying to participants.
Debriefing – After any study, the researcher talks with participants and educates them about the
research process.
Data Fabrication – when researchers invent data that fit their hypotheses.
Data falsification – when researchers influence a study’s results, perhaps by selectively deleting
observations from a data set or by influencing their research subjects to act in a hypothesized way.
Plagiarism – representing the ideas or words of others as one’s own. “The appropriation of another
person’s credit”.
Self-plagiarism – recycling portions of own scientific work by scientists.
Chapter 10: Experimentele studies
Taking notes: more effective to take notes by hand for conceptual learning (Mueller & Oppenheimer,
2014)
Motivating babies: “A baby seeing an adult who works hard to achieve his goal stimulates to more
effort than a baby seeing an adult succeed effortlessly” (Leonard et al., 2017)
Experiment – manipulating at least one variable and measuring another.
Manipulated variable – a variable that is controlled, such as when the researchers assign participants
to a particular level (value) of the variable.
Measured variable – measured variables in the form of records of behavior or attitudes, such as self-
reports, behavioral observations, or physiological measures.
Independent variable – the manipulated (causal) variable in an experiment: the researcher has some
“independence” in assigning people to different levels of this variable.
Conditions – the ‘levels’ of a study
dependent variable / outcome variable – the measured variable: how a participant acts on the
measured variable depends on the level of the independent variable.
, Control variable – a variable that an experimenter holds constant on purpose, to test internal validity;
to rule out alternative explanations.
A well-designed experiment – establishing temporal precedence by manipulating the independent
variable, which (virtually) ensures the that the cause comes before the effect.
Confounds – alternative explanations, a potential threat to internal validity.
Design confound – an experimenter’s mistake in designing the independent variable, whereby a
second variable happens to vary systematically along with the intended independent variable,
creating an alternative explanation for the results.
Systematic variability – when a second variable varies systematically along with the independent
variable. Only then, it is considered a confound.
Unsystematic variability – when a second variable varies along with the independent variable random
or haphazard. This is not considered a confound.
Selection effects – when the kinds of participants in one level (group) of the independent variable are
systematically different from those in the other. This makes it impossible to tell the reason for the
result of an experiment, posing a threat for internal validity.
Random assignment – a way of avoiding selection effects by desystematizing the types of participants
who end up in each level of the independent variable, creating a situation in which the experimental
groups will become virtually equal, on average, before the independent variable is applied.
Matched groups – a way of avoiding selection effects by sorting participants from lowest to highest
on some variable, grouping them into sets of two, and assigning the participants within the sets at
random to the two experimental groups. This makes sure that the experimental groups are as equal
as possible before the independent variable is applied.
Construct validity:
Aspects of good measurement of dependent variables:
1. Face validity – checking if the methods constitute good measures of the conceptual variables
for example by giving an example.
2. Interrater reliability – using to coders to grade the same questions to check for similar scores
between these coders.
3. Manipulation check
Manipulation check – an extra dependent variable that researchers can insert into an experiment to
convince them that their experimental manipulations worked. It’s (likely to be) used when the
intention is to make participants think or feel certain ways.
Pilot study – a simple study, using a separate group of participants, that is completed before (or
sometimes after) the study of primary interest to confirm the effectiveness of the manipulations.
Construct validity and theory testing – the construct validity of an experiment requires an evaluation
how well the manipulations and measures used in a study capture the conceptual variables in a
theory.
External validity of causal claims (other people) – interrogated to generalize a causal claim, at least to
the population of interest, by asking about random sampling: randomly gathering a sample from a
population.
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